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    KNOWLEDGE POWER DETECTOR
    2.
    发明申请
    KNOWLEDGE POWER DETECTOR 审中-公开

    公开(公告)号：US20190236159A1

    公开(公告)日：2019-08-01

    申请号：US15885619

    申请日：2018-01-31

    申请人： Salesforce.com, inc.

    发明人： Raksha Subramanyam ,  Aishwarya Kumar

    IPC分类号： G06F17/30

    CPC分类号： G06F16/24578 ,  G06F16/248 ,  G06F16/252 ,  G06Q10/1053 ,  G06Q10/1095

    摘要： Matching knowledge providers with knowledge consumers. Information corresponding to knowledge providers and information corresponding to knowledge consumers is managed in a database. Messages from remote electronic devices corresponding to the knowledge providers and the knowledge consumers are received. Subsequent information corresponding to the knowledge providers and the knowledge consumers is gathered from a plurality of remote platforms. Knowledge power agents configured to operate through the plurality of interfaces match knowledge providers with knowledge consumers based, at least in part, on shared interests, location and availability. In response to a match between at least one knowledge provider and at least one knowledge consumer, communicating via at least one of the plurality of interfaces information about the match to at least one knowledge consumer and at least one knowledge provider for which the match has been made.

    CREATING AND USING TRIPLET REPRESENTATIONS TO ASSESS SIMILARITY BETWEEN JOB DESCRIPTION DOCUMENTS
    4.
    发明申请
    CREATING AND USING TRIPLET REPRESENTATIONS TO ASSESS SIMILARITY BETWEEN JOB DESCRIPTION DOCUMENTS 审中-公开

    公开(公告)号：US20190197482A1

    公开(公告)日：2019-06-27

    申请号：US15854837

    申请日：2017-12-27

    申请人： International Business Machines Corporation

    发明人： David G. George ,  Sudhanshu S. Singh ,  Joydeep Mondal ,  Sarthak Ahuja ,  John A. Medicke ,  Amanda Klabzuba

    IPC分类号： G06Q10/10 ,  G06F7/02 ,  G06F17/27

    CPC分类号： G06Q10/1053 ,  G06F7/026 ,  G06F17/2705 ,  G06F17/2785

    摘要： A method, system and computer program product for assessing similarity between two job description documents. Job description documents consist of sentences framed in a particular manner, where the sentences are represented as a set of actions, an object corresponding to each action and a set of attributes corresponding to the object. The two job description documents are parsed to generate a first and a second set of an action-object-attribute triplet representation, where the first set of the action-object-attribute triplet representation is associated with the first job description document and the second set of the action-object-attribute triplet representation is associated with the second job description document. A similarity score between the first and second sets of action-object-attribute triplet representations is then calculated by hierarchically matching the first and second sets of action-object-attribute triplet representations across the job description documents. In this manner, similar job positions/job descriptions may be more accurately identified.

    EMBEDDED LEARNING FOR RESPONSE PREDICTION
    5.
    发明申请
    EMBEDDED LEARNING FOR RESPONSE PREDICTION 审中-公开

    公开(公告)号：US20190197398A1

    公开(公告)日：2019-06-27

    申请号：US15855912

    申请日：2017-12-27

    申请人： Microsoft Technology Licensing, LLC

    发明人： Mohsen Jamali ,  Hamed Firooz ,  Samaneh Moghaddam ,  Mahdi Shafiei

    IPC分类号： G06N3/08

    CPC分类号： G06N3/08 ,  G06Q10/1053

    摘要： Techniques for learning and leveraging embeddings for response prediction are provided. Based on training data, an embedding for each attribute value of multiple content items is generated, an embedding for each attribute value of multiple entities is generated, weights of a first neural network for content items is generated, and weights of a second neural network for requesting entities is generated. In response to receiving a request, a particular content item is identified. A first set of embeddings for the particular content item is identified and input into the first neural network to generate first output. A particular requesting entity that initiated the content request is identified. A second set of embeddings for the particular requesting entity is identified and input into the second neural network to generate second output. The particular content item is selected based on the first output and the second output.

    MULTIPLE ELEMENT JOB CLASSIFICATION
    7.
    发明申请
    MULTIPLE ELEMENT JOB CLASSIFICATION 审中-公开

    公开(公告)号：US20190188647A1

    公开(公告)日：2019-06-20

    申请号：US15842443

    申请日：2017-12-14

    申请人： SAP France

    发明人： Jean-Baptiste Gariel ,  Marc Vu ,  Marwan Ajala

    IPC分类号： G06Q10/10 ,  G06Q10/06 ,  G06F17/30

    CPC分类号： G06Q10/1053 ,  G06F16/951 ,  G06F16/955 ,  G06Q10/063112

    摘要： Multiple element job classification data objects include values for multiple elements related to a job. The multiple element job classification data object may be generated automatically from a job listing or search query. A database of multiple element job classification data objects may be created using scraping. Scraping job listing data from multiple job listing sites allows for the creation of a centralized database that includes all job listings from the multiple sites. Converting the job listings from a typical title-and-description format into multiple element job classification data objects permits more accurate searching of the data. The database of multiple element job classification data objects may be searched for relevant job listings by a user who provides a text string. The text string is converted into a multiple element job classification data object and used to find job listings that correspond to the user's search.

    HEURISTICALLY-DRIVEN PLATFORM AND METHOD FOR HIRING BASED ON PREVIOUSLY-SUPPORTED JOBS
    8.
    发明申请
    HEURISTICALLY-DRIVEN PLATFORM AND METHOD FOR HIRING BASED ON PREVIOUSLY-SUPPORTED JOBS 审中-公开

    公开(公告)号：US20180365648A1

    公开(公告)日：2018-12-20

    申请号：US15953796

    申请日：2018-04-16

    申请人： HIREMOJO, INC.

    发明人： John YOUNGER ,  Michael HOWELL

    IPC分类号： G06Q10/10

    CPC分类号： G06Q10/1053

    摘要： A heuristically-driven platform and method for hiring based on previously-supported jobs and collected metrics solves the problem of efficiently connecting hiring agents and suitable job candidates. A portal application includes an inventory of successful placements and successful listings, allowing hiring agents to build job searches against a database of historical jobs. Leveraging the portal's inventory of placements and listings, the hiring agent may build a listing and design a candidate search based on previous listings, search venues for the same job type and metrics collected against each. An embodiment may provide the hiring agent a listing of the hiring agent's jobs, a list of applicants for each listed job and the detail for each applicant. The platform monitors applicant flow, online interviews, and site usage analytics for each position, suggesting alternatives and course corrections to the hiring agent if the performance of the job search is sub-par based on benchmarks.